Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics

Maria A. Rocca; Nicoletta Anzalone; Loredana Storelli; Anna Del Poggio; Laura Cacciaguerra; Angelo A. Manfredi; Alessandro Meani; Massimo Filippi

doi:10.1097/rli.0000000000000735

Back

Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics

Article 2020 en

Abstract

1 min read

A neural network performed better than expert raters in terms of accuracy in classifying white matter disorders from magnetic resonance imaging and may help in their diagnostic work-up.

Discussion(0)

No comments yet. Be the first to comment.

Related publications

Article2002

Magnetic Resonance Imaging of Multiple Sclerosis

Massimo Filippi, Carla Tortorella, Marco Rovaris

Article2000

The value of new magnetic resonance techniques in multiple sclerosis

Marco Rovaris, Massimo Filippi

Article2022

A Deep-Learning Approach to Predicting Disease Progression in Multiple Sclerosis Using Magnetic Resonance Imaging (P1-1.Virtual)

Loredana Storelli, Matteo Azzimonti, Mor Gueye, Paolo Preziosa, Gioacchino Tedeschi, Nicola De Stefano, Patrizià Pantano, Massimo Filippi, Maria A. Rocca

Article1996

Magnetic resonance imaging in the differential diagnosis and monitoring of the treatment of multiple sclerosis

Massimo Filippi, David H. Miller

Article1998

Unenhanced and enhanced magnetic resonance imaging in the diagnosis of multiple sclerosis.

Franz Fazekas, Frederik Barkhof, Massimo Filippi